Ready for eHealth? Health professionals' acceptance and adoption of eHealth interventions in inpatient routine care

Hennemann, Severin; Beutel, Manfred E.; Zwerenz, Rüdiger

doi:10.1080/10810730.2017.1284286

Cited by 274Telemedicine and Telehealth ImplementationMobile Health and mHealth ApplicationsHealth Literacy and Information Accessibility

Ready for eHealth? Health professionals' acceptance and adoption of eHealth interventions in inpatient routine care

Hennemann, Severin, Beutel, Manfred E., Zwerenz, Rüdiger·2017·Journal of Health Communication

DOI 10.1080/10810730.2017.1284286

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Abstract

eHealth interventions can be effective in treating health problems. However, adoption in inpatient routine care seems limited. The present study therefore aimed to investigate barriers and facilitators to acceptance of eHealth interventions and of online aftercare in particular in health professionals of inpatient treatment. A total of 152 out of 287 health professionals of various professional groups in four inpatient rehabilitation facilities filled out a self-administered web-based questionnaire (response rate: 53%); 128 individuals were eligible for further data analysis. Acceptance and possible predictors were investigated with a complex research model based on the Unified Theory of Acceptance and Use of Technology. Acceptance of eHealth interventions was rather low (M = 2.47, SD = 0.98); however, acceptance of online aftercare was moderate (M = 3.08, SD = 0.96, t(127) = 8.22, p < .001), and eHealth literacy was elevated. Social influence, performance expectancy, and treatment-related internet and mobile use significantly predicted overall acceptance. No differences were found between professional and age groups. Although acceptance of eHealth interventions was limited in health professionals of inpatient treatment, moderate acceptance of online aftercare for work-related stress implies a basis for future implementation. Tailored eHealth education addressing misconceptions about inferiority and incongruity with conventional treatment considering the systemic aspect of acceptance formation are needed.

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Perceived Drivers and Barriers to the Adoption of eMental Health by Psychologists: The Construction of the Levels of Adoption of eMental Health Model
Feijt, M. A., de Kort, Y. A., Bongers, I. M., & IJsselsteijn, W. A. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9485 · Cited by 134 · see citing works
“Thus, a random sample drawn from this population, typical for survey studies, includes only a small percentage of active users and a much larger percentage of nonusers (eg, [22,34-37]).”
BackgroundInfluential
Changing Behavior Using the Model of Action Phases
Keller, L., Gollwitzer, P. M., & Sheeran, P. (2020) · The Handbook of Behavior Change · doi:10.1017/9781108677318.006 · Cited by 147 · see citing works
Modeling predictors of acceptance and use of electronic medical record system in a resource limited setting: Using modified UTAUT model
Shiferaw, K., & Mehari, E. A. (2019) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2019.100182 · Cited by 136 · see citing works
The Role of Telehealth During the COVID-19 Pandemic Across the Interdisciplinary Cancer Team: Implications for Practice
Paterson, C., Bacon, R., Dwyer, R., Morrison, K. S., Toohey, K., O'Dea, A., Slade, J., Mortazavi, R., Roberts, C., Pranavan, G., et al. (2020) · Seminars in Oncology Nursing · doi:10.1016/j.soncn.2020.151090 · Cited by 139 · see citing works
Psychotherapists’ Challenges With Online Therapy During COVID-19: Concerns About Connectedness Predict Therapists’ Negative View of Online Therapy and Its Perceived Efficacy Over Time
Békés, V., Aafjes-van Doorn, K., Luo, X., Prout, T. A., & Hoffman, L. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.705699 · Cited by 134 · see citing works
Theories Informing eHealth Implementation: Systematic Review and Typology Classification
Heinsch, M., Wyllie, J., Carlson, J., Wells, H., Tickner, C., & Kay-Lambkin, F. (2021) · Journal of Medical Internet Research · doi:10.2196/18500 · Cited by 114 · see citing works
Changing Behavior Using the Health Action Process Approach
Schwarzer, R., & Hamilton, K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.007 · Cited by 107 · see citing works
Intention to use electronic medical record and its predictors among health care providers at referral hospitals, north-West Ethiopia, 2019: using unified theory of acceptance and use technology 2(UTAUT2) model
Ahmed, M. H., Bogale, A. D., Tilahun, B. C., Kalayou, M. H., Klein, J., Mengiste, S. A., & Endehabtu, B. F. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01222-x · Cited by 104 · see citing works
Available tools to evaluate digital health literacy and engagement with eHealth resources: A scoping review
Faux‐Nightingale, A., Philp, F., Chadwick, D. D., Singh, B. M., & Pandyan, A. D. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e10380 · Cited by 92 · see citing works
“Most studies used surveys [14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49] administered as online questionnaires [24, 26, 29, 41, 43, 45, 47], paper questionnaires [16, 17, 26, 38, 39, 40, 41, 50, 51], administered their su…”
BackgroundMethod
Internet- and mobile-based aftercare and relapse prevention in mental disorders: A systematic review and recommendations for future research
Hennemann, S., Farnsteiner, S., & Sander, L. (2018) · Internet Interventions · doi:10.1016/j.invent.2018.09.001 · Cited by 86 · see citing works
Educational interventions and their effects on healthcare professionals’ digital competence development: A systematic review
Kulju, E., Jarva, E., Oikarinen, A., Hammarén, M., Kanste, O. I., & Mikkonen, K. (2024) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2024.105396 · Cited by 113 · see citing works
Attitudes of General Practitioners Toward Prescription of Mobile Health Apps: Qualitative Study
Sarradon‐Eck, A., Bouchez, T., Auroy, L., Schuers, M., & Darmon, D. (2021) · JMIR mhealth and uhealth · doi:10.2196/21795 · Cited by 81 · see citing works
“Rather than the classical opposition found in the literature between “resistance to” [30-33] and “acceptance of” [34-37] digital health technologies, Marent et al [29] prefer to use the concept of ambivalence as a “means of facilitating and capturing contradictions and tensions in accounts of…”
Background
Determinants of the behavioral intention to use a mobile nursing application by nurses in China
Pan, M., & Gao, W. (2021) · BMC Health Services Research · doi:10.1186/s12913-021-06244-3 · Cited by 90 · see citing works
Healthcare professionals’ digital health competence and its core factors; development and psychometric testing of two instruments
Jarva, E., Oikarinen, A., Andersson, J., Tomietto, M., Kääriäinen, M., & Mikkonen, K. (2023) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2023.104995 · Cited by 78 · see citing works
Digital Interventions for Mental Disorders: Key Features, Efficacy, and Potential for Artificial Intelligence Applications
Ebert, D. D., Harrer, M., Apolinário-Hagen, J., & Baumeister, H. (2019) · Advances in Experimental Medicine and Biology · doi:10.1007/978-981-32-9721-0_29 · Cited by 76 · see citing works
Habit Interventions
Gardner, B., Rebar, A. L., & Lally, P. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.041 · Cited by 69 · see citing works
Physiotherapists’ use and perceptions of digital remote physiotherapy during COVID-19 lockdown in Switzerland: an online cross-sectional survey
Osthoff, A.-K. R., Baur, H., Reicherzer, L., Wirz, M., Keller, F., Opsommer, E., Schoeb, V., Vercelli, S., & Barbero, M. (2021) · Archives of Physiotherapy · doi:10.1186/s40945-021-00112-3 · Cited by 68 · see citing works
Upscaling e-mental health in Europe: a six-country qualitative analysis and policy recommendations from the eMEN project
Gäebel, W., Lukies, R., Kerst, A., Stricker, J. H., Zielasek, J., Diekmann, S., Trost, N., Gouzoulis‐Mayfrank, E., Bonroy, B., Cullen, K., et al. (2020) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-020-01133-y · Cited by 68 · see citing works
Internet use and eHealth literacy among health-care professionals in a resource limited setting: a cross-sectional survey
Shiferaw, K. B., & Mehari, E. A. (2019) · Advances in Medical Education and Practice · doi:10.2147/amep.s205414 · Cited by 66 · see citing works
“Although it was not on the regression table, Internet use significantly predicted the eHealth literacy of health professionals, which coincides with other research.(42)Finally, although the majority of health professionals have access to the Internet, most of them do not use it for finding health information from cred…”
BackgroundResult
Willingness to Use Digital Health Tools in Patient Care Among Health Care Professionals and Students at a University Hospital in Saudi Arabia: Quantitative Cross-sectional Survey
Thapa, S., Nielsen, J. B., Aldahmash, A. M., Qadri, F. R., & Leppin, A. (2021) · JMIR Medical Education · doi:10.2196/18590 · Cited by 65 · see citing works
“This may partly be a consequence of an often narrow scope of individual studies, due to an exclusive focus on specific tools, such as telemedicine [9-12] and electronic medical record [13,14], one professional group (often medical doctors) [8,14-16], or one medical specialty [17-20].”
BackgroundResult
Healthcare providers’ readiness for electronic health record adoption: a cross-sectional study during pre-implementation phase
Ngusie, H. S., Kassie, S. Y., Chereka, A. A., & Enyew, E. B. (2022) · BMC Health Services Research · doi:10.1186/s12913-022-07688-x · Cited by 88 · see citing works
Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study
Apolinário-Hagen, J., Hennemann, S., Fritsche, L., Drüge, M., & Breil, B. (2019) · JMIR Mental Health · doi:10.2196/15373 · Cited by 63 · see citing works
“Generally, most research on the UTAUT model point to performance expectancy as the strongest driver of technology acceptance across different contexts and innovations [47-49], including eHealth services [34,46,50-52].”
Self-citation
Changing Behavior Using Social Cognitive Theory
Łuszczyńska, A., & Schwarzer, R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.003 · Cited by 71 · see citing works
Debunking the myth of industry 4.0 in health care: insights from a systematic literature review
Cavallone, M., & Palumbo, R. (2020) · The TQM Journal · doi:10.1108/tqm-10-2019-0245 · Cited by 59 · see citing works
Systematic AI Support for Decision-Making in the Healthcare Sector: Obstacles and Success Factors
Bertl, M., Ross, P., & Draheim, D. (2023) · Health Policy and Technology · doi:10.1016/j.hlpt.2023.100748 · Cited by 59 · see citing works
Healthcare professionals' digital health competence profiles and associated factors: A cross‐sectional study
Jarva, E., Oikarinen, A., Andersson, J., Pramila‐Savukoski, S., Hammarén, M., & Mikkonen, K. (2024) · Journal of Advanced Nursing · doi:10.1111/jan.16096 · Cited by 54 · see citing works
Self-Efficacy Interventions
Warner, L. M., & French, D. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.032 · Cited by 53 · see citing works
Usage and perceptions of telemedicine among health care professionals in China
Ma, Q., Sun, D., Tan, Z., Li, C., He, X., Zhai, Y., Wang, L., Cui, F., Li, M., Gao, J., et al. (2022) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2022.104856 · Cited by 52 · see citing works
Online therapy: an added value for inpatient routine care? Perspectives from mental health care professionals
Sander, J., Bolinski, F., Diekmann, S., Gäebel, W., Günther, K., Hauth, I., Heinz, A., Kleiboer, A. M., Riper, H. M., Trost, N., et al. (2021) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-021-01251-1 · Cited by 52 · see citing works
“In accordance with the present results, previous studies demonstrated that a severe course of disease [11, 17] and insufficient (technical) infrastructure [16] are perceived obstacles that prevent mental health professionals from using digital interventions in Germany and other Western societies [18].”
Acceptance and barriers to access of occupational e-mental health: cross-sectional findings from a health-risk population of employees
Hennemann, S., Witthöft, M., Bethge, M., Spanier, K., Beutel, M. E., & Zwerenz, R. (2018) · International Archives of Occupational and Environmental Health · doi:10.1007/s00420-017-1280-5 · Cited by 49 · see citing works
Self-citation
Changing Behavior Using Ecological Models
Salmon, J., Hesketh, K. D., Arundell, L., Downing, K. L., & Biddle, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.017 · Cited by 51 · see citing works
Application of the unified theory of acceptance and use of technology model to predict dental students’ behavioral intention to use teledentistry
Alabdullah, J. H., Lunen, B. L. V., Claiborne, D. M., Daniel, S. J., Yen, C., & Gustin, T. S. (2020) · Journal of Dental Education · doi:10.1002/jdd.12304 · Cited by 49 · see citing works
Integrating technology in mental healthcare practice: A repeated cross-sectional survey study on professionals’ adoption of Digital Mental Health before and during COVID-19
Feijt, M. A., de Kort, Y. A. W., Westerink, J. H. D. M., Bierbooms, J. J. P. A., Bongers, I. M. B., & IJsselsteijn, W. A. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1040023 · Cited by 49 · see citing works
“For long, the adoption of DMH in practice remained at a stable and low level (7, 9).”
Background
A narrative synthesis systematic review of digital self-monitoring interventions for middle-aged and older adults
Bartels, S. L., van Knippenberg, R. J. M., Dassen, F. C. M., Asaba, E., Patomella, A.-H., Malinowsky, C., Verhey, F. R. J., & de Vugt, M. E. (2019) · Internet Interventions · doi:10.1016/j.invent.2019.100283 · Cited by 45 · see citing works
Experiences of Online Counseling Among Undergraduates in Some Ghanaian Universities
Amos, P. M., Bedu-Addo, P. K. A., & Antwi, T. (2020) · SAGE Open · doi:10.1177/2158244020941844 · Cited by 46 · see citing works
“in treating health problems; about four out of five internet users report to seeking counseling on health-related issues online (Hennemann et al., 2017; Uzoekwe et al., 2012).”
Background
Digital health competencies and affecting factors among healthcare professionals: additional findings from a systematic review
Longhini, J., Rossettini, G., & Palese, A. (2024) · Journal of research in nursing · doi:10.1177/17449871241226899 · Cited by 45 · see citing works
“Good use of the Internet and mobiles for treatments, performance expectancy and social influence have resulted as being associated with a good level of e-health acceptance (Hennemann et al., 2017).”
Background
Changing Behavior Using Self-Determination Theory
Hagger, M. S., Hankonen, N. E., Chatzisarantis, N. L. D., & Ryan, R. M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.008 · Cited by 49 · see citing works
Comparing the Acceptance of Mobile Hypertension Apps for Disease Management Among Patients Versus Clinical Use Among Physicians: Cross-sectional Survey
Breil, B., Salewski, C., & Apolinário-Hagen, J. (2021) · JMIR Cardio · doi:10.2196/31617 · Cited by 45 · see citing works
“Although the UTAUT model was developed in the business context, it is being extensively used to understand acceptance of new health care technologies [19], for instance, by assessing the usage intentions of a specific health technology among patients [20,21] and physicians [17,22].”
BackgroundMethod
Experience of coronary heart disease patients with a nurse-led eHealth cardiac rehabilitation: Qualitative process evaluation of a randomized controlled trial
Su, J. J., Paguio, J. T., Baratedi, W. M., Abu‐Odah, H., & Baťalík, L. (2022) · Heart & Lung · doi:10.1016/j.hrtlng.2022.10.005 · Cited by 44 · see citing works
Health Care Professionals’ Attitudes Toward, and Experiences of Using, a Culture-Sensitive Smartphone App for Women with Gestational Diabetes Mellitus: Qualitative Study
Garnweidner-Holme, L. M., Andersen, T. H., Sando, M. W., Noll, J., & Lukasse, M. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9686 · Cited by 37 · see citing works
“The findings of this study showed high levels of acceptance of mHealth among the participants, and this was in agreement with a previous study [31].”
BackgroundResultInfluential
Adaptation and Implementation of a Mobile Phone–Based Remote Symptom Monitoring System for People With Cancer in Europe
Furlong, E., Darley, A., Fox, P., Buick, A. R., Kotronoulas, G., Miller, M., Flowerday, A., Miaskowski, C. A., Patiraki, E. I., Katsaragakis, S., et al. (2018) · JMIR Cancer · doi:10.2196/10813 · Cited by 45 · see citing works
“On the basis of previous research that showed clinicians’ concern and apprehension about new eHealth technologies [47-49], the feasibility study of the ASyMS helped the research team identify clinicians’ concerns and provide additional training sessions that afforded clinicians the opportunity to learn about the study…”
Background
Predicting acceptance of e-mental health interventions in patients with obesity by using an extended unified theory of acceptance model: Cross-sectional study
Rentrop, V., Damerau, M., Schweda, A., Steinbach, J., Schüren, L. C., Niedergethmann, M., Skoda, E.-M., Teufel, M., & Bäuerle, A. (2022) · JMIR Formative Research · doi:10.2196/31229 · Cited by 42 · see citing works
A multi-stakeholder approach to eHealth development: Promoting sustained healthy living among cardiovascular patients
Breeman, L. D., Keesman, M., Atsma, D. E., Chavannes, N. H., Janssen, V., van Gemert-Pijnen, L., Kemps, H., Kraaij, W., Rauwers, F., Reijnders, T., et al. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104364 · Cited by 37 · see citing works
“Thus, already in the early development phase, researchers should focus on stakeholder acceptance and engagement to ensure a good fit with user needs and preferences [11,12].”
Background
Use of telemedicine in the outpatient sector during the COVID-19 pandemic: a cross-sectional survey of German physicians
Knörr, V., Dini, L., Gunkel, S., Hoffmann, J., Mause, L., Ohnhäuser, T., Stöcker, A., & Scholten, N. (2022) · BMC Family Practice · doi:10.1186/s12875-022-01699-7 · Cited by 41 · see citing works
“found a negative correlation of health professional’s age with the perception of telemedicine’s significance [18, 19].”
Background
Supporting medication adherence for adults with cystic fibrosis: a randomised feasibility study
Hind, D., Drabble, S. J., Arden, M. A., Mandefield, L., Waterhouse, S., Maguire, C., Cantrill, H., Robinson, L., Beever, D., Scott, A. J., et al. (2019) · BMC Pulmonary Medicine · doi:10.1186/s12890-019-0834-6 · Cited by 39 · see citing works
Planning and Implementation Intention Interventions
Rhodes, R. E., Grant, S. J., & de Bruijn, G. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.039 · Cited by 41 · see citing works
Attitudes and Persuasive Communication Interventions
Hamilton, K., & Johnson, B. T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.031 · Cited by 40 · see citing works
Changing Behavior Using Habit Theory
Orbell, S., & Verplanken, B. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.013 · Cited by 39 · see citing works
Investigating the use of digital health tools in physiotherapy: facilitators and barriers
Keel, S., Schmid, A., Keller, F., & Schoeb, V. (2022) · Physiotherapy Theory and Practice · doi:10.1080/09593985.2022.2042439 · Cited by 39 · see citing works
“…and Emerson, 2001), become a “competent member” (Pollner and Emerson, 2001) of the studied community (see the notion of unique adequacy introduced by Garfinkel (1967)), or just spend short periods in the field to get a general grasp of the studied setting and/or to conduct theory-driven,…”
Background
Changing Behavior: A Theory- and Evidence-Based Approach
Hagger, M. S., Cameron, L. D., Hamilton, K., Hankonen, N. E., & Lintunen, T. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.001 · Cited by 39 · see citing works
Social Identity Interventions
Tarrant, M., Haslam, C., Carter, M., Calitri, R., & Haslam, S. A. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.044 · Cited by 37 · see citing works
Changing Behavior Using Integrated Theories
Hagger, M. S., & Hamilton, K. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.015 · Cited by 39 · see citing works
A bibliometric analysis on global eHealth
Tian, H., & Chen, J. (2022) · Digital Health · doi:10.1177/20552076221091352 · Cited by 35 · see citing works
“Health care professionals needed eHealth education and support for health consumers,(16) especially how to obtain and evaluate the quality of health information,(17) so as to effectively treat health problems through eHealth interventions.(18) Emerging universal eHealth access provided immense societal benefits in reg…”
Background
Digitale Gesundheitsanwendungen (DiGA) in der ärztlichen und psychotherapeutischen Versorgung. Chancen und Herausforderungen aus Sicht der Leistungserbringer
Gerlinger, G., Mangiapane, N., & Sander, J. (2021) · Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz · doi:10.1007/s00103-021-03408-8 · Cited by 33 · see citing works
Health Care Providers’ Acceptance of a Personal Health Record: Cross-sectional Study
Yousef, C. C., Salgado, T. M., Farooq, A., Burnett, K., McClelland, L. E., Esba, L. C. A., Alhamdan, H. S., Khoshhal, S., Aldossary, I., Alyas, O. A., et al. (2021) · Journal of Medical Internet Research · doi:10.2196/31582 · Cited by 33 · see citing works
“MNGHA Care will increase patient satisfaction with their health care [48].”
Influential
Improving Acceptability and Uptake Behavior for Internet-Based Cognitive-Behavioral Therapy
Molloy, A., Ellis, D. M., Su, L., & Anderson, P. L. (2021) · Frontiers in Digital Health · doi:10.3389/fdgth.2021.653686 · Cited by 29 · see citing works
Changing Behavior Using the Transtheoretical Model
DiClemente, C. C., & Graydon, M. M. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.010 · Cited by 31 · see citing works
eHealth literacy and its associated factors in Ethiopia: Systematic review and meta-analysis
Wubante, S. M., Tegegne, M. D., Melaku, M. S., Kalayou, M. H., Tarekegn, Y. A., Tsega, S. S., Mengestie, N. D., Demsash, A. W., & Walle, A. D. (2023) · PLoS ONE · doi:10.1371/journal.pone.0282195 · Cited by 31 · see citing works
Changing Behavior Using the Health Belief Model and Protection Motivation Theory
Orbell, S., Zahid, H., & Henderson, C. J. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.004 · Cited by 32 · see citing works
Association between expectations and clinical outcomes in online v. face-to-face therapy – an individual participant data meta-analysis
Pontén, M., Jonsjö, M. A., Vadenmark, V., Moberg, E., Grannas, D., Andersson, G., Boersma, K., Hedman‐Lagerlöf, E., Kleinstäuber, M., Weise, C., et al. (2023) · Psychological Medicine · doi:10.1017/s0033291723003033 · Cited by 31 · see citing works
“…et al., 2015; Mohr et al., 2010) and that Internet-based cognitive behavioral therapy is heavily underutilized (Carper, McHugh, & Barlow, 2013; Hennemann, Beutel, & Zwerenz, 2017) [although showing comparable efficacy with face-to-face (Carlbring, Andersson, Cuijpers, Riper, &…”
Changing Behavior by Changing Environments
Marteau, T. M., Fletcher, P. C., Hollands, G. J., & Munafo, M. R. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.014 · Cited by 27 · see citing works
<p>Current practices of health care providers in recommending online resources for chronic pain self-management</p>
Devan, H., Godfrey, H., Perry, M., Hempel, D., Saipe, B., Hale, L., & Grainger, R. (2019) · Journal of Pain Research · doi:10.2147/jpr.s206539 · Cited by 26 · see citing works
Acceptance of e-mental health services for different application purposes among psychotherapists in clinical training in Germany and Switzerland: secondary analysis of a cross-sectional survey
Braun, P., Drüge, M., Hennemann, S., Nitsch, F. J., Staeck, R., & Apolinário-Hagen, J. (2022) · Frontiers in Digital Health · doi:10.3389/fdgth.2022.840869 · Cited by 27 · see citing works
“, “I have the necessary preconditions for using the following EMH service”) were measured each with two items that were partly adapted from previous studies (28, 33).”
BackgroundMethodResultInfluential
Exploring user-related drivers of the early acceptance of certified digital stress prevention programs in Germany
Apolinário-Hagen, J., Hennemann, S., Kück, C., Wodner, A., Geibel, D., Riebschläger, M., Zeißler, M., & Breil, B. (2020) · Health Services Insights · doi:10.1177/1178632920911061 · Cited by 26 · see citing works
Utilization of e-mental-health and online self-management interventions of patients with mental disorders—A cross-sectional analysis
Webelhorst, C., Jepsen, L., & Rummel‐Kluge, C. (2020) · PLoS ONE · doi:10.1371/journal.pone.0231373 · Cited by 27 · see citing works
“In order to examine the interest for digital therapeutic services with the presented study, we aimed to determine the impact of internet use in patients with mental disorders in a sample of German patients, since the digital world is rapidly growing [21].”
Background
The Acceptance of Digital Health: What about Telepsychology and Telepsychiatry?
Alhur, A., & Alhur, A. A. (2022) · Jurnal Sistem Informasi · doi:10.21609/jsi.v18i2.1143 · Cited by 28 · see citing works
“Research findings on telepsychology and telepsychiatry are in accordance with the extensive literature on the acceptance and use of new technology, particularly eHealth acceptance and use (Hennemann et al., 2017; Mattila et al., 2017)”
Result
Cancer Survivors’ Receptiveness to Digital Technology–Supported Physical Rehabilitation and the Implications for Design: Qualitative Study
Rossen, S., Kayser, L., Vibe-Petersen, J., Christensen, J. F., & Ried‐Larsen, M. (2020) · Journal of Medical Internet Research · doi:10.2196/15335 · Cited by 26 · see citing works
Design, Implementation, and Evaluation of Behavior Change Interventions: A Ten-Task Guide
Abraham, C., & Denford, S. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.019 · Cited by 26 · see citing works
Changing Behavior Using the Reflective-Impulsive Model
Deutsch, R., & Strack, F. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.012 · Cited by 28 · see citing works
Readiness to use electronic medical record systems and its associated factors among health care professionals in Ethiopia: A systematic review and meta-analysis
Walle, A. D., Shibabaw, A. A., Tilahun, K. N., Atinafu, W. T., Adem, J. B., Demsash, A. W., Baykemagn, N. D., Kebede, S. D., Ferede, T. A., Tegegne, M. D., et al. (2022) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2022.101140 · Cited by 26 · see citing works
eHealth in Geriatric Rehabilitation: An International Survey of the Experiences and Needs of Healthcare Professionals
Kraaijkamp, J. J. M., Persoon, A., Aurelian, S. M., Bachmann, S., Cameron, I. D., Choukou, M.-A., Dockery, F., Eruslanova, K. A., Gordon, A. L., Grund, S., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12134504 · Cited by 26 · see citing works
“Barriers can be overcome with continuing education for healthcare professionals, a modernized education of healthcare students that includes eHealth awareness, as well as co-creation and behavior change techniques that should be part of any implementation strategy [23,28].”
BackgroundResult
Dyadic Behavior Change Interventions
Scholz, U., Berli, C., Lüscher, J., & Knoll, N. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.043 · Cited by 23 · see citing works
Developing Behavior Change Interventions
Hankonen, N. E., & Hardeman, W. (2020) · Cambridge University Press eBooks · doi:10.1017/9781108677318.021 · Cited by 26 · see citing works
Patient-reported outcome measures obtained via E-Health tools ease the assessment burden and encourage patient participation in cancer care (PaCC Study)
Erickson, N. T., Schinköthe, T., Eckhardt, C., Storck, L. J., Joos, A., Liu, L., Ballmer, P. E., Mumm, F., Fey, T., & Heinemann, V. (2021) · Supportive Care in Cancer · doi:10.1007/s00520-021-06351-1 · Cited by 23 · see citing works
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Authors: Hennemann, S., Beutel, M. E., & Zwerenz, R.
Affiliations: Johannes Gutenberg University Mainz (DE)
University Medical Center of the Johannes Gutenberg University Mainz (DE)
Corresponding author: Hennemann, Severin
ORCID: Hennemann, Severin
Beutel, Manfred E.
Zwerenz, Rüdiger
Venue: Journal of Health Communication
Publisher: Informa UK Limited
Published: 2017-02-19
Volume: 22
Issue: 3
Pages: 274-284
ISSN: 1081-0730 (ISSN-L)
1087-0415
DOI: 10.1080/10810730.2017.1284286
OpenAlex: W2587843908
Cited by: 274
References: 70
Citations by year: 2026: 20 · 2025: 16 · 2024: 24 · 2023: 33 · 2022: 44 · 2021: 35 · 2020: 71 · 2019: 18 · 2018: 10 · 2017: 3
FWCI: 26.28
Type: journal article
Language: en
Open access: closed
Locations: Journal of Health Communication (publishedVersion)
PubMed (publishedVersion)
Funders: Illa and Werner Zarnekow Foundation (T225-22.771)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
Keywords: digital health interventions, healthcare workers, technology acceptance, inpatient care, Unified Theory of Acceptance and Use of Technology, digital health literacy, barriers and facilitators, inpatient rehabilitation, occupational stress, social influence, performance expectancy
MeSH terms: Adult, Cross-Sectional Studies, Female, Health Personnel, Hospitalization, Humans, Male, Middle Aged, Telemedicine, Health Care Surveys, Young Adult

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Ready for eHealth? Health professionals' acceptance and adoption of eHealth interventions in inpatient routine care

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